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The utilization of artificial intelligence has been demonstrated in the literature to be effective for classification and prediction. Nevertheless, the application of k-Nearest Neighbour (k-NN) and Artificial Neural Network (ANN) specifically the conventional feed forward Multilayer Perceptron (MLP) model for forecasting and scouting of high-performance archers have not been fully utilized. The current investigation predicted high and low-performance archers from a set of selected fitness and motor skill parameters trained on two distinct machine learning algorithms viz. ANN and k-NN.

A sample of 50 youth archers with the average age and standard deviation of (17.0 ± 0.56) recruited from varying youth archery schemes completed a one end archery score test. Standardize physical fitness and motor skill parameters measurements constituting of the hand grip, vertical jump, standing broad jump, static …